Promoting new habits at work through implementation intentions

Trenz, Nina; Keith, Nina Article — Published Version Promoting new habits at work through implementation intentions Journal of Occupational and Organizational Psychology Provided in Cooperation with: John Wiley & Sons Suggested Citation: Trenz, Nina; Keith, Nina (2024) : Promoting new habits at work through implementation intentions, Journal of Occupational and Organizational Psychology, ISSN 2044-8325, Wiley Periodicals, Inc., Hoboken, NJ, Vol. 97, Iss. 4, pp. 1813-1834, https://doi.org/10.1111/joop.12540 This Version is available at: https://hdl.handle.net/10419/313810 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by-nc/4.0/ J Occup Organ Psychol. 2024;97:1813–1834. | 1813 wileyonlinelibrary.com/journal/joop BACKGROUND More than 100 years ago, William James stated that “habit covers a very large part of life” (James, 1890, p. 104). Today, habits are still considered fundamental in guiding and controlling daily life. Habits facilitate automatic behaviours, which are executed without cognitive effort (Gardner, 2015; Gardner & Lally, 2023; Wood & Neal, 2007). As modern work environments place a variety of complex demands Received: 17 July 2023 | Accepted: 24 July 2024 DOI: 10.1111/joop.12540 RESEARCH ARTICLE Promoting new habits at work through implementation intentions Nina Trenz | Nina Keith This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2024 The Author(s). Journal of Occupational and Organizational Psycholog y published by John Wiley & Sons Ltd on behalf of The British Psychological Society. Department of Human Sciences, Technical University of Darmstadt, Darmstadt, Germany Correspondence Nina Trenz, Department of Human Sciences, Technical University of Darmstadt, Alexanderstraße 10, 64283 Darmstadt, Germany. Email: [email protected] Abstract Habits facilitate automatic behaviours and are resource efficient. Habits at work may be beneficial because they conserve cognitiveattentional resources, thus fostering work engagement and goal progress. In a diary intervention study (2 daily assessments, 10 work days), we asked 72 employees to establish a new habit at work. Half of them additionally completed an intervention on the correct use of implementation intentions. All participants were given access to a followup survey. In multilevel analyses, automaticity of the new habitual behaviour predicted work engagement and goal progress at the daylevel. Implementation intentions predicted frequency of the habitual behaviour and in turn increased automaticity of this behaviour. The effects of implementation intentions were still evident at followup. Contrary to expectations, the intervention did not increase participants' daily use of implementation intentions. The results indicate that implementation intentions might be used in everyday work to establish habits at work, thus increasing employees' efficiency and engagement. KEYWORDS automatic behaviour, goal progress, ifthen planning, work engagement, work routines 1814 | TRENZ and KEITH on employees, it seems highly desirable to save resources through automatic behaviours by establishing habits at work. In contrast to habits in other areas of psychological interest, such as health or environmental behaviour (Bamberg, 2002; Gardner, 2015; Gardner et al., 2011, 2012; Holland et al., 2006), habits at work have received little attention in organizational psychology (for exceptions, see Chae & Choi, 2019; Ohly et al., 2017; Sonnentag et al., 2022). We propose that habits at work increase goal progress and work engagement because they save cognitiveattentional resources (Danner et al., 2007, 2008; Gardner et al., 2012), such as directive attention and working memory capacity (Kanfer & Ackerman, 1989; Kanfer et al., 2017). This is because habits generate behaviours (i.e., habitual behaviours) that are triggered by the context and thus performed automatically (Gardner & Lally, 2023). We further propose that implementation intentions are a strategy to implement new habits fast and deliberately (Gollwitzer, 1999, 2014). Implementation intentions represent a planning strategy in which a specific situation is linked to an action, specifying exactly when, where and how the action will be performed, for example, “When I have finished work, then I will clean up my desk” (Gollwitzer, 1999, 2012). Implementation intentions have been widely used as a powerful tool for habit formation and habit change, particularly in the context of health psychology (Adriaanse & Verhoeven, 2018; Bamberg, 2002; Verplanken & Faes, 1999; Webb et al., 2010). Implementation intentions drive habit formation because they facilitate action initiation in the specified situations, thus increasing the frequency of an intended behaviour in this situation (Gollwitzer, 1999, 2014; Keller et al., 2020). As habits develop through constant repetition of behaviours in consistent contexts (Lally et al., 2010, 2011), this increased frequency of a specific behaviour in a specific situation may promote habit formation. Our study contributes to the literature in several ways. We extend recent findings that unwanted habits at work can be reduced with implementation intentions (Sonnentag et al., 2022). We use the strategy of implementation intentions to build new habits at work and focus on the consequences of these new habits for employee's work engagement and goal progress. That is, our study focuses on more distal dependent variables, whereas previous research on habits and implementation intentions at work focused on habit formation as outcome and did not include trickledown effects of habits. By considering trickledown effects of habits, we further seek to show that habits can improve selfregulation at work. For this reason, we focus on habit effects on work engagement and goal progress, that is, on outcomes of successful selfregulation at work (Lord et al., 2010; Parke et al., 2018). In addition, we seek to further explore the causal relationship between implementation intentions and habit formation. To this end, we applied an intervention (i.e., mental contrasting with implementation intentions) designed to increase the use of implementation intentions (Adriaanse et al., 2010; Clark et al., 2021; Oettingen et al., 2015). We derive our hypotheses from theories of habit formation (Gardner et al., 2016; Lally et al., 2010; Wood & Neal, 2007) and research on implementation intentions (Gollwitzer, 1999, 2012). Our research hypotheses are depicted in Figure 1. Habits at work Habits are learned behavioural dispositions that are automatically triggered by features of the context in which that specific behavioural pattern has been performed frequently and consistently (Lally Practitioner points • Establishing habits at work relates to higher employee engagement and effectiveness. • Implementation intentions are a planning strategy that supports employees in establishing and maintaining habits at work. | 1815 PROMOTING HABITS AT WORK & Gardner, 2013; Wood & Neal, 2007). Habits are dependent on a contextual cue (Arlinghaus & Johnston, 2018; Ohly et al., 2006, 2017). Hence, widely different behaviours can become habitual if they are regularly performed in the same context and thereby linked to contextual cues (Lally et al., 2010). The term habit refers to a cognitive construct, that is, the association between context and behaviour, while the term habitual behaviour refers to behaviour generated by a habit (Gardner & Lally, 2023). Habits and habitual behaviour can also occur at work (Ohly et al., 2006, 2017; Sonnentag et al., 2022). Based on the general definition of habits, we define habits at work as behavioural dispositions that people learn at work and that are automatically triggered by specific features of the work context. Work habits can be distinguished in taskrelated habits, habits related to the interpersonal context of work, and nonworkspecific habits (Sonnentag et al., 2022). Taskrelated habits refer to the core job task and represent behavioural dispositions relevant for task performance (Borman & Motowidlo, 1993), for example, fixed writing times. Contextually embedded habits refer to the interpersonal context of work and particularly involve contextual performance (Borman & Motowidlo, 1993), for example, shared coffee breaks which encourage group cohesion and productivity (Maspul, 2024; Stroebaek, 2013). Non workspecific habits are dispositions for behaviours that people engage in at work but that do not necessarily relate to the job, for example, selfreward via healthy or unhealthy snacks (Sonnentag et al., 2022). As each of these habit types can be relevant for performance and wellbeing at work, all of them fall within the scope of this study. In this study, we assessed the frequency and automatization of an observable behaviour that people show at work. Hence, our hypotheses refer to habitual behaviour at work. Positive consequences of habits at work Automaticity is a central characteristic of habits (Gardner et al., 2012; Lally & Gardner, 2013; Wood & Neal, 2007). More specifically, habitual action control changes from a conscious motivational process to a contextdriven mechanism (Gardner, 2015; Lally et al., 2010). Habits are triggered automatically in the presence of a corresponding contextual cue, that is, an external stimulus, a thought, or an emotion (Lally & Gardner, 2013; Wood & Neal, 2007). Habitual behaviours can consequently be fast and efficient and they are executed without conscious thought and effort (Seger & Spiering, 2011; Wood & Rünger, 2016). Due to their automaticity, habitual behaviours can be beneficial because they save cognitiveattentional resources such as directive attention and working memory capacity (Chae & Choi, 2019; Morgan & Hancock, 2011; Ohly et al., 2006; Voss et al., 2008). Cognitiveattentional resources are limited in availability, meaning that the more resources invested in a task, the better performance on that task will be, while performance on other tasks will decline FIGURE 1 Proposed model. Note: The dashed arrow represents an indirect effect. Implementation Intentions Frequency Automaticity Work Engagement Goal Progress H2a H1a H2b H1b H3 Brief Intervention H4 1816 | TRENZ and KEITH (Kanfer & Ackerman, 1989; Kanfer et al., 2017). Hence, saving cognitiveattentional resources through automatic behaviours means that more of these resources can be invested in other cognitively demanding tasks (Chae & Choi, 2019; Ohly et al., 2006). In the work context, evidence that automatic behaviours save cognitiveattentional resources is empirically supported by related research on work routines. Specifically, this research showed that work routines are associated with free cognitive resources (Chae & Choi, 2019) or higher levels of energy (Ohly et al., 2017) and positively related to creativity in highly complex jobs (Chae & Choi, 2019; Ohly et al., 2006). Similarly, morning routine disruptions have been shown to enhance cognitive depletion and in turn decrease work engagement and goal progress (McClean et al., 2021). Routines are observable repetitive behaviours at work that are regularly carried out in the same way and in the same order (McClean et al., 2021; Piscitello et al., 2019). Routines are similar to habits because both refer to automatic behaviour that is induced by contextual cues (Ohly et al., 2017). However, routines are more complex behavioural sequences that involve sequencing and combining processes, procedures, steps, or occupations which are typically performed by groups rather than individuals. That is, routines have habitual elements, but not all habits are routines (Clark, 2000). Like routines, habits at work might save cognitiveattentional resources, consequently fostering work engagement and goal progress. Work engagement Work engagement, which is defined as a positive, fulfilling, workrelated state of mind (Schaufeli et al., 2002), generally depends on resources (Bakker & Demerouti, 2007, 2008; Crawford et al., 2010; Demerouti & Bakker, 2023). That is, employees may be more or less engaged on a specific day depending on resource availability (Tims et al., 2011; Xanthopoulou et al., 2009). In the present study, we refer to resources as cognitiveattentional resources allocated to tasks during goalstriving (Kanfer & Ackerman, 1989; Kanfer et al., 2017). Work engagement is characterized by vigour, dedication, and absorption (Schaufeli et al., 2002). Vigour refers to high levels of energy while working. Dedication means being strongly involved in one's work, and absorption refers to a state of being fully concentrated and happily engrossed in work (Bakker & Demerouti, 2008). An engaged state requires the presence of energy to be invested in the work tasks, and being fully absorbed in work requires shielding against potential distractors that employees face on a daily basis (Kahn, 1990; McClean et al., 2021). Habitual behaviours at work save cognitiveattentional resources and time due to their automaticity (Chae & Choi, 2019; Morgan & Hancock, 2011; Ohly et al., 2006; Voss et al., 2008). This results in a higher level of energy to be invested in work tasks (McClean et al., 2021; Ohly et al., 2017), thus fostering work engagement. Hypothesis 1a. Automaticity of the new habitual behaviour during the workday is positively related to daily work engagement. Goal progress Progress towards a work goal varies within persons, depending on how well cognitiveattentional resources such as directive attention are allocated to the work task within a given episode (Beal et al., 2005; Koopman et al., 2016). The more time is spent on task accomplishment and the more attention is focused on the task, the easier goal progress will be (Beal et al., 2005; Kahneman, 1973). Cognitiveattentional resources saved by automatization increase the cognitive slack and save time, both of which can then be invested in other tasks (Chae & Choi, 2019; Morgan & Hancock, 2011; Ohly et al., 2017; Voss et al., 2008). In addition, habitual behaviour at work might in itself bring positive effects for work performance in terms of goal progress. For example, useful taskrelated habits such as fixed writing | 1817 PROMOTING HABITS AT WORK times or turning off the mail program at certain times might facilitate habitual behaviours that reduce multitasking or taskswitching, which has a positive impact on work performance in the shortterm and longterm (Junco & Cotten, 2012; Monsell, 2003; Paridon & Kaufmann, 2010). Hypothesis 1b. Automaticity of the new habitual behaviour during the workday is positively related to daily goal progress. Implementation intentions and habit formation Implementation intentions (see Gollwitzer, 1993, 1999, 2014) are plans that specify when, where, and how one will initiate goaldirected behaviours. Various studies show that implementation intentions promote the formation of new habits as well as the abandonment of unwanted ones (Gollwitzer & Sheeran, 2006) with regard to health goals (Adriaanse & Verhoeven, 2018; Verplanken & Faes, 1999; Webb et al., 2010) and to environmental goals (Bamberg, 2002; Holland et al., 2006). In the work context, one study has shown that implementation intentions can change non workspecific habits such as recycling behaviour (Holland et al., 2006). Another recent study demonstrated that implementation intentions can reduce detrimental taskrelated habits (i.e., habits interfering with work goals), such as task switching, that are enacted at the workplace (Sonnentag et al., 2022). These positive effects of implementation intentions are thought to occur because implementation intentions facilitate action initiation of an intended behaviour (Gollwitzer & Sheeran, 2006; Keller et al., 2020), thus promoting constant repetition of this behaviour in a specific context. Implementation intentions support the initiation of an intended habitual behaviour in a specific context because they facilitate the shift in action control from topdown to bottomup processes (Bieleke et al., 2021). This is because implementation intentions facilitate encoding and recall of situational cues (Janczyk et al., 2015) and thus increase awareness of these situational, or contextual, cues (Achtziger et al., 2012). In addition, implementation intentions strengthen the mental connection between a situation and a specific behaviour, so that this behaviour is automatically activated whenever encountering the previously defined situation (Keller et al., 2020; Webb & Sheeran, 2007). Consequently, implementation intentions increase the likelihood that a specific behaviour will be performed in a specific situation. In other words, implementation intentions can increase the frequency with which a certain behaviour (a new habit) is performed in a certain situation (a consistent context). The regular repetition of a specific behaviour in a specific context is supposed to increase the automatization of this behaviour in this context, thus creating a habit (Lally et al., 2010, 2011). Hypothesis 2. Forming implementation intentions in the beginning of the workday is positively related to (a) frequency and (b) automaticity of the new habitual behaviour. Hypothesis 3. The relationship between forming implementation intentions and automaticity of the new habitual behaviour is mediated by frequency of this behaviour. As described in the previous sections, it seems desirable to establish habits at work. Because implementation intentions promote habit formation and thus might increase effectivity and engagement at work, increasing the use of implementation intentions can be of high practical relevance. From a methodological perspective, manipulating the independent variable increases the internal validity of a study. Interventions that increase the use of implementation intentions open up the possibility to manipulate this variable experimentally, which raises confidence in the causal direction of action (e.g., implementation intentions increase the use of habits and not vice versa). For these two reasons, we aimed at increasing the use of implementation intentions in our study within an intervention group and compare the effects against a control group. In the following, we describe how implementation intentions might 1818 | TRENZ and KEITH be enhanced with an economic intervention and explain how mental contrasting can contribute to enhancing the use of implementation intentions. Generally, the strategy of implementation intentions is considered easy to teach due to its simplicity (Keller et al., 2020). Consistent with this assumption, multiple studies demonstrated the effectiveness of interventions with implementation intentions (for metaanalyses, see Gollwitzer & Sheeran, 2006; Keller et al., 2020; Sheeran et al., 2024). The effectiveness of these interventions, and in particular the motivation to use implementation intentions, can be further enhanced by combining them with mental contrasting (Adriaanse et al., 2010; Clark et al., 2021; Duckworth et al., 2018; Oettingen et al., 2015). In these combined interventions, the achievement of a goal is first imagined as positively as possible. The resulting desired state is then contrasted with reality (i.e., mental contrasting), revealing possible obstacles that can then be circumvented with an ifthen plan (Gollwitzer & Oettingen, 2019). For our purposes, the main advantage of combining these two strategies is that mental contrasting is supposed to increase the willingness to form implementation intentions. That is, combining implementation intentions with mental contrasting helps to ensure that implementation intentions will actually be applied after the intervention (Duckworth et al., 2011, 2018). Hypothesis 4. A brief intervention (i.e., mental contrasting with implementation intentions) increases forming implementation intentions to establish a new habit at work. MATERIALS AND METHODS Transparency and openness We describe our sampling plan, all data exclusions, manipulations, and the measures in the study. Data, analysis code and supplemental materials are available at https:// resea rchbox. org/ 1740. Data were analysed using R (Version 4.2.2), the package lme4 (Version 1.131; Bates et al., 2015), the package mediation (Version: 4.5.0; Tingley et al., 2014) and lavaan (Version 0.613; Rosseel, 2012). Preregistration of this study's design and its analyses are available at https:// aspre dicted. org/ ri5mt. pdf.1 Procedures were in line with ethical standards of the German Psychological Society (DGPs), which constitute the German adaptation of the APA's respective ethical guidelines. Formal approval by an ethics committee was not required, as according to the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), formal approval for psychological research is mandatory only in certain cases (e.g., if participants are exposed to pain, to deception, or to risks that go beyond those of everyday life). Informed consent was obtained from all participants at the first time of measurement. Deviations from preregistration We initially aimed for a sample size of 100 participants to find a good middle ground between Level1 and Level2 power. Because of practical constraints (e.g., sharp decline in the number of study registrations despite intensive recruiting efforts), we were not able to acquire more than 72 participants. In general, the power for Level1 effects in diary studies is usually rather too high than too low (Gabriel et al., 2019). For example, 30 Level2 units (i.e., people) and five Level1 units (i.e., days) are sufficient to achieve a power of .80 for a medium Level1 effect at a medium ICC. In contrast, 100 Level2 and 12 Level1 units are necessary to achieve a power of .80 for a medium effect at Level 2 (Arend & Schäfer, 2019, Table 8). Accordingly, the 1We refer to the effects of the intervention (Hypothesis 4) in the preregistration only indirectly in the analyses section, but not in the hypotheses section. | 1819 PROMOTING HABITS AT WORK deviation from the planned sample size did not limit the power for the reported Level1 effects. However, the power for Level2 effects, that is, the effect of the intervention, may have been limited.2 We decided not to include the last preregistered hypothesis, which deals with the role of feedback (in terms of goal progress) for forming implementation intentions, in the manuscript because it renders the research question of the manuscript too broad and complex. That is, this hypothesis reverses dependent and independent variables which, in retrospect, did not seem reasonable to us within the same study. The results of this hypothesis test are documented in the section “Additional Analyses”. In addition, we decided in the review process to revise the position of automaticity and frequency within our theoretical model, as this direction of effect is more in line with the habit literature. This resulted in slight changes of Hypotheses 1 and 3. Sample and procedure The study consisted of three parts: (1) the initial survey that included the intervention, (2) the twopart daily survey (morning and evening over 10 days), and (3) the followup (two weeks later). In the initial survey, 203 subjects (94 in the intervention group) participated. During the dailysurvey period, these participants completed 700 morning questionnaires and 669 evening questionnaires. Eighty of these participants completed the followup survey. We matched the surveys, using the serial number assigned to each person by the survey software. Only individuals who had completed both the initial measurement and the daily survey while missing no more than three days of the daily survey were included in the final sample. In addition, we included several nonsense items as attention checks (Meade & Craig, 2012). One person answered one of these items incorrectly during the initial measurement and was excluded. Further, we excluded four daily surveys because, here, the persons answered the attention check item incorrectly within the respective afternoon survey. The final sample included 611 complete pairs of questionnaires (morning and evening) from 72 participants (34 in the intervention group, 38 in the control group). Followup data were available from 63 of these participants. Participants (61% female, 39% male) were employees from various industries, who we approached through social networks (Xing, LinkedIn, Facebook) and the personal networks of the investigators. We decided to examine one particular occupational field to minimize possible contextual influences. That is, we focused on typical office workers because we assumed that the daily schedule in this work area is predictable and selfdetermined enough to establish fixed individual habits. To ensure such a work environment, the participants had to fulfil three requirements: work at least five days per week, perform the work activity primarily on a computer, and have access to the Internet at least 50% of the work time. Additionally, we used only complete data sets for the hypothesis tests (no missing variables).3 The majority of participants had a bachelor's or master's degree (68%) and worked in an employed relationship (89%). The industries represented were quite heterogeneous, with the provision of economic, financial, scientific, technical or other services being the most represented (49%). Eleven percent worked in public administration, defence or social security, and 8% in manufacturing or processing. 2We examined the power for the Level2 effect of the intervention post hoc on the basis of the empirical ICC. More specifically, we conducted a sensitivity analyses or analysis of the minimum detectable effect size (MDES analysis), adapting the code provided by Arend & Schäfer (2019, Example 1). An MDES analysis is used to calculate the smallest detectable effect size as a function of power, sample size, and α, as well as in the case of twolevel models, the ICC of the dependent variable (Arend & Schäfer, 2019). The empirical ICC of implementation intentions (i.e., which was our primary dependent variable for the expected intervention effects) was .49, which corresponds to a large ICC. Following conventions, we set α at .05 and power at .80. The resulting MDES for the intervention effect was a medium effect, γstd = .34. In other words, the MDES analysis indicated that with the given sample size of 72 and an ICC of .49, the intervention effect had to be .34 or larger to be detected in our study. 3The multilevel mediation analyses with the package mediation (Version: 4.5.0; Tingley et al., 2014) required complete data sets. We additionally tested all other hypotheses with incomplete data sets (i.e., allowing for missing variables within a day). The results did not alter our conclusions. 1820 | TRENZ and KEITH Most participants had been working in this industry for a long time (49% for more than 10 years) and were longtime tenured with this employer (40% for more than 10 years). We conducted the study online, that is, participants accessed the different parts of the study via links sent to them. In the first part, we asked participants to identify an appropriate workrelated habit that they would establish over the next two weeks. For this purpose, they could first choose from four different goal categories and were then supported in their habit selection with examples of appropriate habits. After participants had selected their habit, we randomized them into two groups, of which one received a brief intervention (i.e., exercise on mental contrasting with implementation intentions; we will describe this exercise in more detail below). The control group instead reflected on their work environment. In the second part, all participants completed 5min questionnaires in the morning and evening over a twoweek period (i.e., ten workdays), always starting on Monday. Participants received the morning surveys at 7 a.m. and the evening surveys at 5 p.m. The third part was a onetime followup survey on the key dependent variables two weeks after the end of the daily survey. We chose this time period of two weeks for the followup to be able to explore longerterm effects with as little data loss as possible. Because the duration of complete automatization of a behaviour is highly individual (Lally et al., 2010), we were unable to derive an optimal time period from existing literature. Further, we expected increasing dropout rates with longer time intervals. Measures We used established measures and made some adaptations. First, we adjusted the time frame of daily scales so that they referred specifically to the day (Ohly et al., 2010). Second, we used items in German language. To keep the response format constant for all scales, participants rated all items on a 5point scale from 1 (strongly disagree) to 5 (totally agree). If available, we used corresponding German versions of the questionnaires. If not, two members of our research group fluent in German and English translated the items into German. In this process, two persons (first author of this paper and a graduate student) first translated the items independently, discussed discrepancies, and agreed on a first version (i.e., parallel translation; Smith, 2004). A third person (second author of this paper) proofread this version of the translation and made final suggestions for changes. The first two persons discussed these suggestions again and integrated them in a final version. In the initial survey, we assessed different characteristics of occupation and person that we expected to influence habit formation as potential control variables. The inclusion of these control variables, as we will explain later, did not alter the results or conclusions. In the morning survey, we assessed implementation intentions as well as positive and negative affect as potential control variables. We further asked participants to name their selected habit in this survey. In the evening survey, we assessed frequency and automaticity of the habitual behaviour, goal progress, and work engagement. In the followup survey, we assessed frequency and automaticity of the habitual behaviour, goal progress, and work engagement again, but with the focus on the past two weeks. Implementation intentions We measured whether participants had formulated implementation intentions on a given day with a scale consisting of five items, as used by Sonnentag et al. (2022). This scale essentially captures whether a plan has been made for “when”, “where” and “how” the new habitual behaviour will be applied and whether a specific place and time has been specified. A sample item is: “I have planned for today how I can show my new habit.” Internal consistencies were high, ranging between .91 and .97. | 1827 PROMOTING HABITS AT WORK Control variables We replicated the hypothesis tests with the addition of the control variables. We found no evidence for an influence of these variables on the hypothesized relationships (see Tables S1 and S2). Habit type To rule out the possibility that the results were influenced by the type of goal category and the associated nature of habitual behaviour, we created three dummy variables to represent the four goal categories and analysed main effects and crosslevel interactions. We found no evidence for an influence of goal category (or habit type) on the postulated relationships. However, daily goal progress was higher for participants who had selected the goal category “work more effectively” than for the other participants, unstandardized estimate = .48, SE = .20, p = .015 (see Table S3). Relationship between automaticity and frequency Theories of habit formation suggest that automaticity of the new habitual behaviour might increase over the course of the study. This is because the participants acquired this behaviour anew and the automatization of a behaviour is supposed to increase with constant repetition (Gardner, 2015; Lally et al., 2010, 2011). Accordingly, we conducted a singlefactor repeated measures analysis of variance with linear contrasts to analyse the time trend of automaticity. This analysis revealed a linear increase in automaticity over the course of the daily survey, unstandardized estimate = 16.88, SE = 3.26, F(1, 40) = 28.36, p < .001. Serial mediation Our theoretical model could imply serial mediation in which implementation intentions increase the work outcomes via the frequency of the new habitual behaviour via automaticity of the new habitual behaviour. We conducted two serial mediation analyses that showed significant indirect effects of implementation intentions via frequency via automaticity on work engagement, b = .01, SE = .01, p = .014, 95% CI [.003, .023] and goal progress, b = .02, SE = .01, p = .004, 95% CI [.006, .030]. DISCUSSION This research explored whether habits at work can increase goal progress and work engagement as well as whether and how the establishment of these habits can be increased through implementation intentions. Results showed that engaging in habitual behaviours at work positively relates to daily work engagement and daily goal progress. Furthermore, results indicated that implementation intentions promote frequency and automaticity of such habitual behaviours. Theoretical implications First, the results contribute to habit literature by demonstrating positive effects of habitual behaviours in a rather new context. Extensive research on habits in other (particularly in health) contexts shows that a large part of selfregulatory processes (i.e., action initiation and execution) is controlled by habitual processes (Lally & Gardner, 2013). For example, a metaanalysis showed that eating habits have a stronger influence 1828 | TRENZ and KEITH on eating behaviour than conscious intention (Gardner et al., 2011). Our finding that habitual behaviours at work promote work engagement and goal progress demonstrates that the shift from a conscious motivational process to a contextdriven mechanism associated with this type of behaviour (Gardner, 2015; Lally et al., 2010) also facilitates selfregulation at work. This is because both work engagement and goal progress are the result of successful selfregulation (Lord et al., 2010; Parke et al., 2018). As both work engagement and goal progress are associated with various positive outcomes such as job satisfaction, organizational commitment or decreased burnout (Bipp et al., 2020; Judge et al., 2005; Koestner et al., 2002; Mazzetti et al., 2023; Wong et al., 2017), our results imply that habitual behaviours at work might have a wide positive impact. Regarding the applicability of habits in the work context, our study extends research that revealed positive relationships of the related construct of work routines with creativity (Chae & Choi, 2019; Ohly et al., 2006). This is because our results indicate that habitual behaviours are beneficial not only for specific, creative tasks, but possibly applicable in a broader range of work areas and tasks. Second, this study demonstrates that implementation intentions promote habit formation at work. Specifically, we extend previous research, demonstrating that habits at work can be modified by implementation intentions (Holland et al., 2006; Sonnentag et al., 2022) because we consider the relationship between automaticity and frequency at the daylevel. Our study illustrates that the daily use of implementation intentions increases the frequency of a new behaviour in a specific situation and in turn the automaticity of this behaviour. Additional analyses further showed that automaticity of the new habitual behaviour increased over the course of the study. Taken together, these results indicate that implementation intentions promote constant repetition of a behaviour in the same context and thereby accelerate the process of habit formation. Our results also allow for tentative conclusions about the longerterm impact of implementation intentions. Consistent with other results (Sonnentag et al., 2022), the positive effects of implementation intentions were also evident at followup. Individuals who had formed implementation intentions to a higher extent within the daily survey phase reported higher work engagement, higher goal progress, and higher frequency and automaticity of the habitual behaviour two weeks later. Studies disagree on the durability of the effects of implementation intentions. On the one hand, withindesigns with discontinuous presentation of implementation intentions suggest that the effects of implementation intentions decline rapidly (Breitwieser et al., 2021; Luers et al., 2019). In these studies, implementation intentions only affected behaviour on days when participants received the prompt to form implementation intentions. On the other hand, betweendesigns show that effects of interventions with implementation intentions on outcomes are detectable even two years later (Brandstätter et al., 2003; Martin et al., 2011). Even though the followup survey period was comparatively short at two weeks, our results suggest that the effects of implementation intentions do not disappear immediately, but are durable for a longer period of time. Practical implications Our findings further provide practical insights for organizations and individuals. Results show that the establishment of habits at work can be used to increase goal progress and engagement at work. Hence, employees might be encouraged to promote habits at work that are consistent with work goals (and that at the same time do not interfere with important personal goals). This could be achieved by educating employees in training courses or elearning about the positive impact habits can have on their productivity and wellbeing. In addition, the results imply that implementation intentions contribute to habit formation in the work context. Hence, implementation intentions might be used in practice to improve individual habits at work. In theory, implementation intentions are very easy to teach (Keller et al., 2020). Numerous exercises exist that employees can use to learn this planning strategy. These exercises can be provided in different formats such as online versus facetoface (Keller et al., 2020; Oettingen et al., 2015). In this regard, the online exercise we conducted showed no effects. As positive effects of similar exercises in facetoface training have been demonstrated (Adriaanse et al., 2010; Oettingen et al., 2015), we would | 1829 PROMOTING HABITS AT WORK recommend teaching the strategy in facetoface formats, for example, in corresponding workshops or training. Limitations By using an exercise on mental contrasting with implementation intentions, we sought to manipulate the extent to which individuals formulate implementation intentions to establish a new habit. However, we did not find an intervention effect which is inconsistent with other studies in which effects were achieved with very similar interventions (Adriaanse et al., 2010; Clark et al., 2021; Oettingen et al., 2015). We cannot provide a definitive explanation from the available data. However, as mentioned earlier, other studies differ from ours in that they chose a facetoface format instead of an online format. It is possible that motivation was lower in an online format or that the instructions were not sufficiently understood. Another explanation could be that we asked all participants, including those in the control group, daily whether they had formulated implementation intentions. Asking about implementation intentions might have prompted participants in the control group to form implementation intentions, resulting in the nonsignificant group differences. This design choice may have contributed to the lack of effectiveness of our intervention. One possibility to control for questionbehaviour effects (Wood et al., 2016) is the inclusion of several control days on which participants do not receive questionnaires on implementation intentions and including day of data collection as a control variable in the multilevel analyses, as has been done in other studies (Sonnentag et al., 2022). Apart from these methodological limitations, it is possible that the intervention did not increase the formation of implementation intentions because people used this strategy to varying degrees irrespective of the intervention. In fact, recent studies show that there are interindividual differences in the tendency to formulate implementation intentions that are relatively stable over time (Bieleke & Keller, 2021). As the intervention did not have the expected effects, our results are now based on a correlational design capturing implementation intentions in the beginning of the workday and frequency and automaticity of the habitual behaviour, work engagement, as well as goal progress at the end of the workday. Consequently, we were unable to test a causal effect of implementation intentions on frequency of the habitual behaviour. We further relied on selfreport measures and did not separate the measurement points for mediator and criterion. This means that we examined some of the independent variables (automaticity, frequency) and dependent variables (work engagement, goal progress) at the same time and with the same method. Hence, it cannot be ruled out that a common method bias led to the overestimation of these effects (Podsakoff et al., 2003, 2012). Future research directions We did not test the mechanism directly that the relationship between habitual behaviours and work outcomes might be explained by higher availability of cognitiveattentional resources. As previous studies relied on selfreport (Chae & Choi, 2019; McClean et al., 2021; Ohly et al., 2017), an investigation of this mechanism with different methods would be beneficial. Future studies could, for example, incorporate cognitively demanding tasks to objectively measure the availability of cognitiveattentional resources. As our study provides further evidence that implementation intentions promote the establishment of habits at work, it is of great interest to find alternative means to encourage the use of implementation intentions. For example, it would be valuable to compare different intervention formats (online vs. facetoface training) in further studies or to expand interventions to include other elements such as daily prompts. 1830 | TRENZ and KEITH CONCLUSION In a diary intervention study, we showed that automaticity of a new habitual behaviour at work was associated with higher work engagement and goal progress at the daylevel. Daily implementation intentions predicted daily frequency and automaticity of this habitual behaviour. However, this relationship was independent of the intervention implemented. Habits at work facilitate automatic behaviours that positively relate to employee engagement and efficiency. Implementation intentions represent a promising strategy for promoting habits at work, the antecedents of which might be further explored. AUTHOR CONTRIBUTIONS Nina Trenz: Conceptualization; methodology; formal analysis; writing – original draft; writing – review and editing; visualization; investigation; project administration. Nina Keith: Conceptualization; methodology; writing – review and editing; supervision; project administration; resources. ACKNOWLEDGEMENTS We would like to thank Eva Kircher for data collection. Open Access funding enabled and organized by Projekt DEAL. CONFLICT OF INTEREST STATEMENT The authors declare that they have no conflict of interest. DATA AVAILABILITY STATEMENT The data that support the findings of this study are openly available at https:// resea rchbox. org/ 1740. ORCID Nina Trenz https://orcid.org/0000-0003-4060-1233 REFERENCES Achtziger, A., Bayer, U. C., & Gollwitzer, P. M. (2012). Committing to implementation intentions: Attention and memory effects for selected situational cues. Motivation and Emotion, 36(3), 287–300. https:// doi. org/ 10. 1007/ s1103 101192616 Adriaanse, M. 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